Covid Report for Family

Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	North Dakota	144,846
2	Rhode Island	143,659
3	South Dakota	140,545
4	Utah	127,516
5	Tennessee	124,506
6	Arizona	121,643
7	Iowa	118,011
8	Wisconsin	116,133
9	Nebraska	115,667
10	South Carolina	115,496
11	Oklahoma	114,788
12	New Jersey	114,705
13	Arkansas	113,730
14	Delaware	112,201
15	Indiana	111,641
16	Alabama	111,587
17	Illinois	109,747
18	Kansas	108,867
19	Florida	108,477
20	Idaho	108,264
21	New York	108,260
22	Mississippi	107,144
23	Minnesota	106,992
24	Nevada	106,123
25	Montana	105,539
26	Wyoming	105,418
27	Georgia	103,903
28	Kentucky	103,611
29	Massachusetts	102,804
30	Texas	102,397
31	Louisiana	102,204
32	Missouri	101,067
33	Michigan	99,597
34	Connecticut	97,697
35	New Mexico	97,251
36	California	96,174
37	North Carolina	96,112
38	Colorado	95,874
39	Alaska	95,693
40	Pennsylvania	94,684
41	Ohio	94,623
42	West Virginia	90,865
43	Virginia	79,365
44	Maryland	76,286
45	New Hampshire	72,839
46	District of Columbia	69,643
47	Washington	58,418
48	Puerto Rico	54,108
49	Maine	50,921
50	Oregon	48,442
51	Vermont	38,965
52	Hawaii	25,088

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	Washington	138
2	Wyoming	137
3	Texas	122
4	Colorado	111
5	Missouri	104
6	Louisiana	96
7	Montana	96
8	Utah	96
9	Nevada	92
10	Kentucky	81
11	Arkansas	79
12	Oregon	71
13	Idaho	68
14	North Dakota	59
15	Indiana	58
16	West Virginia	56
17	Alabama	55
18	Arizona	55
19	Maine	46
20	Georgia	45
21	North Carolina	43
22	Mississippi	40
23	Pennsylvania	38
24	Kansas	37
25	New Mexico	37
26	Rhode Island	35
27	Michigan	34
28	Ohio	33
29	Delaware	31
30	Alaska	30
31	Hawaii	30
32	Illinois	30
33	Wisconsin	29
34	Iowa	28
35	South Carolina	28
36	New Jersey	27
37	Oklahoma	27
38	Tennessee	26
39	California	25
40	Minnesota	25
41	New Hampshire	24
42	New York	24
43	South Dakota	23
44	Virginia	23
45	Connecticut	21
46	District of Columbia	19
47	Maryland	18
48	Massachusetts	18
49	Nebraska	17
50	Vermont	17
51	Puerto Rico	12
52	Florida	0

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New Jersey	2,963
2	New York	2,720
3	Massachusetts	2,601
4	Rhode Island	2,569
5	Mississippi	2,468
6	Arizona	2,437
7	Connecticut	2,316
8	Alabama	2,294
9	South Dakota	2,290
10	Louisiana	2,288
11	Pennsylvania	2,147
12	Michigan	2,072
13	New Mexico	2,049
14	Indiana	2,036
15	North Dakota	2,031
16	Illinois	2,006
17	Arkansas	1,940
18	Iowa	1,931
19	Georgia	1,923
20	South Carolina	1,895
21	Oklahoma	1,851
22	Nevada	1,824
23	Tennessee	1,815
24	Texas	1,794
25	Kansas	1,763
26	Delaware	1,724
27	Florida	1,721
28	Ohio	1,712
29	District of Columbia	1,611
30	California	1,610
31	Kentucky	1,607
32	Maryland	1,598
33	Missouri	1,594
34	West Virginia	1,589
35	Montana	1,532
36	Wisconsin	1,375
37	Minnesota	1,343
38	Virginia	1,320
39	Nebraska	1,300
40	North Carolina	1,265
41	Wyoming	1,252
42	Idaho	1,185
43	Colorado	1,181
44	New Hampshire	1,000
45	Puerto Rico	790
46	Washington	767
47	Utah	723
48	Oregon	652
49	Maine	627
50	Alaska	481
51	Vermont	410
52	Hawaii	354

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	West Virginia	5
2	Georgia	3
3	Michigan	3
4	Alabama	2
5	Colorado	2
6	Idaho	2
7	Iowa	2
8	Kentucky	2
9	Missouri	2
10	Oregon	2
11	Pennsylvania	2
12	Wisconsin	2
13	Wyoming	2
14	Arizona	1
15	Illinois	1
16	Indiana	1
17	Louisiana	1
18	Minnesota	1
19	Mississippi	1
20	Montana	1
21	Nevada	1
22	New Jersey	1
23	New Mexico	1
24	North Carolina	1
25	Ohio	1
26	Rhode Island	1
27	South Dakota	1
28	Texas	1
29	Alaska	0
30	Arkansas	0
31	California	0
32	Connecticut	0
33	Delaware	0
34	District of Columbia	0
35	Florida	0
36	Hawaii	0
37	Kansas	0
38	Maine	0
39	Maryland	0
40	Massachusetts	0
41	Nebraska	0
42	New Hampshire	0
43	New York	0
44	North Dakota	0
45	Oklahoma	0
46	Puerto Rico	0
47	South Carolina	0
48	Tennessee	0
49	Utah	0
50	Vermont	0
51	Virginia	0
52	Washington	-2

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
Chattahoochee	Georgia	397,176	1	99
Crowley	Colorado	364,626	2	99
Bent	Colorado	276,851	3	99
Dewey	South Dakota	250,339	4	99
Lincoln	Arkansas	247,006	5	99
Davidson	Tennessee	143,300	191	93
Richland	South Carolina	113,787	998	68
York	South Carolina	113,606	1004	68
Orange	California	85,845	2267	27
Pierce	Washington	61,946	2828	9

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
Foard	Texas	8,658	1	99
Galax city	Virginia	8,350	2	99
Hancock	Georgia	8,159	3	99
Jerauld	South Dakota	7,948	4	99
Emporia city	Virginia	7,856	5	99
Orange	California	1,603	1856	40
York	South Carolina	1,384	2112	32
Richland	South Carolina	1,381	2116	32
Davidson	Tennessee	1,373	2131	32
Pierce	Washington	733	2776	11

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.